Readmission Risk Factors after Hospital Discharge Among the Elderly

Readmission Risk Factors after HospitalDischarge Among the Elderly

Susan Robinson, RN, PhD, Jill Howie-Esquivel, RN, PhD, NP, and David Vlahov, RN, PhD

Abstract

Hospital readmission rates among the elderly are attracting increasing attention. Readmission is costly, es-pecially as proposed new guidelines could deny reimbursement for readmissions. Identifying key factors atdischarge that can serve as prognostic indicators for readmission is an important step toward developing andtargeting interventions to reduce hospital readmissions rates. Published literature has listed predominantlydemographic, clinical, and health care utilization characteristics to describe the factors that put the elderly at risk.However, additional factors are proposed that include social, clinical, individual-level, environmental, andsystem-level factors. Multimodal interventions have been tested and some reduction in readmissions has beenshown. Whether these additional factors might lead to a further reduction remains unclear. In addition topossible factors at discharge, factors identified after the patient has been discharged also must be identified andaddressed. The patient safety literature characterizes factors that put the elderly at risk for adverse drug events,which function as antecedent factors for readmission and likely include the environmental and system-levelfactors. Synthesizing these factors from the readmission and patient safety literature provides the basis todevelop a more comprehensive conceptual framework to identify research gaps aimed at reducing hospitalreadmissions among the elderly. (Population Health Management 2012;15:338–351)

Introduction

Hospital readmission is a growing topic in health carereform and hospitals are taking aim at reducing read-

mission rates and associated costs. The cost to Medicare ofunplanned rehospitalizations in 2004 was $17.4 billionwith 2.3 million, or 20%, of Medicare beneficiaries readmittedto the hospital within 30 days.1 ‘‘Readmission’’ or re-hospitalization is defined as a return to the hospital shortlyafter discharge from a recent hospital stay. Readmission ratestrack how often patients are readmitted to the hospital shortlyafter being discharged and are commonly used as a measureof hospital care.

Prospective and retrospective studies have reported awide range of readmission rates. Although readmissionrates vary in published literature, the elderly (60 years of ageand older) consistently have the highest rate of hospitalreadmission compared to other age groups.2–4 Publishedstudies have associated readmission rates primarily withpatient demographics, chronic conditions, comorbidity, andutilization factors. However, Medicare patients have manymore reasons for readmission to hospitals. Adverse events(AEs), an injury resulting from medical management rather

than the underlying disease, can occur before or duringhospitalization, at discharge, or at home. Moreover, thespecific reasons for readmission caused by AEs may be theresult of patient-related factors, provider factors, or healthsystem-related factors. Medication errors are a major con-tributor to AEs within and outside the hospital setting thatlead to increased health care utilization (ie, clinic visit,emergency department [ED] visit, hospitalization).

According to the 2008 report to Congress, medicationerrors after discharge are not uncommon and contribute toreadmissions.5 Older adults (65 years of age or older) aretwice as likely as others to seek care in EDs for adverse drugevents (ADEs; more than 177,000 emergency visits each year)and are nearly 7 times more likely to be hospitalized after anemergency visit.6 However, providers may not recognize apatient’s symptoms to be the result of an underlying ADE ormay fail to include ADEs as a reason for readmission or asone of the diagnoses. Consequently, identification of ADEs issubject to underreporting and misclassification; therefore, itis less recognized in the readmission literature.

There are similarities in those risk factors associated withmedication errors and with hospital readmissions amongthe elderly in published patient safety and readmission

School of Nursing, University of California, San Francisco, San Francisco, California.

POPULATION HEALTH MANAGEMENTVolume 15, Number 6, 2012ª Mary Ann Liebert, Inc.DOI: 10.1089/pop.2011.0095

338

literatures. Furthermore, the risk factors for medication er-rors also contribute as antecedents to other causes of read-mission. Integrating this information from the readmissionand the patient safety literature may prove useful to identifyrisk factor patterns in readmissions among the elderly.Therefore, the purpose of this article is to summarize thesimilarities and patterns in the literature on the factors thatput the elderly at risk for readmission and at risk for ADEs.This will provide a starting point to identify gaps and areasin need of more research.

A literature search was undertaken, using PubMed andthe Cochrane Database, for articles describing the incidenceof and contributors to readmission after discharge and ofADEs among the elderly. To summarize the factors that putthe elderly at risk for readmission, articles that characterizedor identified the incidence, contributors, and causes of hos-pital readmission or ADEs were selected. These includedreview articles, epidemiological articles, meta-analyses, andclinical investigations. Additionally, prevalence of prescrip-tion use and associated populations were obtained frompublished Web sites such as the Slone Epidemiology Centerand the National Health and Nutrition Examination SurveyWeb site.

This article is organized from a patient-centered focus andaddresses the factors shown in Figure 1.

Incidence of Readmissions and Adverse Drug Events

Adverse drug event rates

In a study conducted between 1990 and 1993, ADEs led tomore than 7000 deaths, 1.5 million injuries, and 700,000 EDvisits per year, which translated to loss of life and more than$77 billion in avoidable health care costs.7 Data from UShealth care facilities reported that approximately 3.5 millionpatients were treated for ADEs in ambulatory care settings.8

Estimates based on extrapolations and meta-analyses indi-cate that up to 1.5 million patients are treated for ADEs inEDs,9 and approximately 1.5 million patients are hospital-ized each year for ADEs.10 More recent population-level es-timates of outpatient ADEs using the National Center forHealth Statistics found that the rate of ADEs is rising, with

more than 4.3 million persons seeking medical care for an AEannually.11 The incidence of ADEs requiring medical treat-ment increased substantially between 1995 and 2005; inparticular, patients ages 65 years and older had an incidenceof ADE visits as high as 1 in 20 persons seeking relatedmedical care.11

Although untoward drug effects concern all segments ofsociety, ADEs are especially prevalent among the elder-ly.9,12,13 The estimated annual population rate of ADEs re-quiring hospitalization was nearly 7 times the rate forpersons younger than 65 years of age.6 Patients aged 65 yearsor older accounted for 37.0% of estimated unintentional in-jury visits requiring hospitalization and 48.9% of estimatedADE visits requiring hospitalization.6 Patients aged 65 yearsor older were more than twice as likely to be treated forADEs in EDs, and more of these visits were made bywomen.6

Readmission rates

Readmission rates are reported mostly at 30-, 60-, or 90-day intervals after discharge. Thirty-day readmission ratesranged from 12% to 19.6%; 90-day readmission rates rangedfrom 23% to 34%, and admission rates related to AEs rangedfrom 13% to 49% (Table 1).1,3,4,6,14–18

Factors that Contribute to Readmission in the Elderly

Risk factors for hospital readmission include socio-demographic and clinical characteristics, individual patient-level factors, environmental trends in outpatient care, andsystem-level factors.

Sociodemographic factors

Sociodemographic factors that contribute to hospitalreadmission encompass age, sex, socioeconomic status, ed-ucation, social support/resources, race/ethnicity, insurance,financial, and access to/availability of services. Some studieshave associated readmission and ADEs among the elderlywith race, sex, and insurance type. Among the elderly, Af-rican American race and Medicaid as payer status were as-sociated with readmission, and drug-related events were

FIG. 1. Conceptual diagram depicting the factors affecting readmission in the elderly.

ELDERLY READMISSION FACTORS 339

higher among women (Table 2).3,9,14,19 However, one studywith a small sample size (n = 142) that included patients aged50 years and older with previous hospitalization did notdetect a significant influence of age and sex on read-mission.16

Clinical characteristics

Health conditions and clinical characteristics (eg, type ofdiagnosis and chronic illnesses, presence of comorbidities,duration of disease, age-related physiological changes) af-fecting pharmacokinetics and pharmacodynamics also areassociated with readmissions. Overall, the most commondiagnoses associated with readmission were heart failure,depression, chronic obstructive pulmonary disease, coagu-lopathy, and diabetes (Table 3).1,3,9,15,16,19,20 In a meta-anal-ysis by Soeken and colleagues, patients with chronic illnesseshad a mean readmission rate of 34%.21 Similarly, patientswith 5 or more medically comorbid conditions had morethan twice the likelihood of an unplanned readmissionwithin 30 days than patients without those conditions 16,20

A cross-sectional study of administrative data from 2002to 2005 containing a maximum of 20 million Medicare andcommercially insured patients for a 1-year period evaluatedpatients for suspected ADEs. This study found that circula-tory, endocrine, nutritional, and metabolic systems ranked

among the top 5 coexisting health problems in hospitalizedpatients.22 Other studies have associated outpatient drug-related harm with patients older than 65 years of age whotake 3 or more medications or specific medications such asdigoxin, warfarin, and insulin.12,23

Medication class

Medication class also was associated with ADEs in thepatient safety literature (Table 4).11,12,24–26 Overall, the mostcommon categories of drugs associated with ADEs wereantimicrobial agents, diabetic agents, and cardiovascularagents. However, none of the ADEs associated with anti-microbials resulted in hospitalization.25

The Beers criterion is a commonly used measure of med-ication appropriateness for older patients.27 A study wasconducted to identify inappropriate use of medications inolder adults and to estimate the risk for ED visits for AEsusing Beers criteria.26 More than half of the estimated EDvisits were related to use of anticholinergics or antihista-mines, nitrofurantoin, or propoxyphene, which are amongthe 41 medications or medication classes always consideredto be potentially inappropriate. Nine of the 10 most com-monly implicated medications for adverse events belongedto 3 classes: oral anticoagulant or antiplatelet agents, antidi-abetic agents, and narrow therapeutic index agents. Together,

Table 1. Readmission Rates

SourceSetting/Study

Population DesignNumber

of Patients

Readmission/Adverse

Event-RelatedAdmission* Rates

Jencks et al,20091

National sample Retrospective: Medicareclaims data from 2003–2004

11,855,702 20% (30-day)34% (90-day)

Wier et al,20114

15 selected states with 42%of the total US population

Retrospective: HCUP data onall-cause readmissions in2008.

8.5 million 19% (30-day)

Joynt et al,201114

Patients discharged fromUS hospitals between2006–2008

Retrospective: NationalMedicare data

3.1 million 13% (30-day)

Allaudeenet al, 20113

550-bed tertiary care academicmedical center. Mean age:59.6 years

Retrospective: observationalstudy of an administrativedatabase

6805 17% (30-day)

Smith et al,200015

Nine VA medical centers Retrospective: secondaryanalysis from RCT

1378 23% (90-day)

Mudge et al,201116

Australian teaching hospital,2006–2007

Prospective cohort study. 142 32%–40%(6-month)39% (90-day)

Bero et al,199117

Medicare patients in acommunity hospital

Retrospective: secondaryanalysis from RCT

706 *35% (90-day)

Budnitz et al,20066

63 US hospitals participatingin the National

Retrospective NEISS-AIP data 701,547 *49%

Electronic Injury SurveillanceSystem–

All Injury Program(NEISS-AIP), 2004–2005

Forster et al,200318

A tertiary care US academichospital.

Prospective cohort study 400 *19%

HCUP, Healthcare Cost and Utilization Project; RCT, randomized controlled trial; VA, Veterans Administration.

340 ROBINSON ET AL.

these 3 classes of medications accounted for an estimated47.5% (95% confidence interval [CI], 40.2%–54.8%) of all EDvisits for ADEs among older adults.26

Number of medications

The patient safety literature has identified that poly-pharmacy is a significant risk factor for ADE-related visits(Table 5).9,11,24,28 Overall, the higher the number of drugsprescribed, the greater the risk of an ADE. Studies examiningdrug categories and patient characteristics among outpatientADEs that lead to ED visits or hospitalizations found that themajority of outpatient harm occurred in patients older than65 years of age who take 3 or more medications; specificdrugs such as digoxin, warfarin, and insulin were implicatedin the majority of instances of outpatient drug-relatedharm.9,12,23 One study found that patients were prescribed alarge number of medications and the more drugs prescribed,the greater the risk of an ADE; however, the risk increasewas not linear, as there was a dramatic increase once patientswere prescribed more than 11 medications.24

Utilization

Readmissions also are characterized by health care utili-zation factors such as visits to the ED, hospitalization, andambulatory primary and specialty care visits (Table 6). 8,9,15,28

Patients are readmitted for a variety of reasons that includetherapeutic management, diagnostic evaluation, rehabilita-tion, prevention, palliation, research, or cosmetic interven-tions. After considering the type of disease and the severitylevel of the patient’s condition, researchers found read-mission rates varied substantially by hospital and by geo-graphic area.1 Although some studies predicted the risk ofreadmission based on previous hospital admissions or EDutilization, a study by Dormann and colleagues29 found thatADEs predicted further readmissions but a lack of ADEs didnot preclude readmissions. In this study, ADEs caused hos-pitalizations in 6.2% of first admissions, and only 4.2% ofhospitalizations were readmissions.29

Patient- and System-Level Factors in Outpatient Care

At the individual level, risk factors or antecedents forreadmission include inadequate self-care behavior skills,disease knowledge, health literacy, and communication, pa-tient adherence, patient choice (intentional and unintention-al), frailty and assistance with activities of daily living, andfollow-up of health care appointments. Similarly, system-level factors such as inadequate communication due to lackof accuracy (eg, medication instructions specifying ‘‘twice aday’’ versus ‘‘after breakfast and after dinner’’), interpreta-tion, completeness, and timeliness of information place thepatient at risk for readmission. Inadequate communicationcan occur between the patient and the health care worker oramong health care providers. Similarly, the availability andaccessibility of resources at a health care setting also influ-ence patient readmissions.

Based on the Congressional Research Service readmissionreport, there is evidence that avoidable medical errors occurwhile patients are in the hospital setting, and that these er-rors can cause AEs following discharge that result in read-missions for some Medicare beneficiaries.5 According to the

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Agency for Healthcare Research and Quality Patient SafetyNetwork, systematic problems in care transitions are at theroot of most AEs that arise after discharge.30 For example,discontinuity between inpatient and outpatient providers iscommon, and studies have shown that traditional communi-cation systems (eg, the dictated discharge summary) generallyfail to reach outpatient providers in a timely fashion and oftenlack essential information. Some studies have implicated as-sessment and communication of unresolved problems at thetime of discharge, inadequate patient education regardingmedications and other therapies, and failure to monitor drugtherapies and overall condition after discharge as contributingto readmissions.18 Moreover, patients frequently receive newmedications or have medications changed during hospitaliza-tions and lack of medication reconciliation results in the po-tential for inadvertent medication discrepancies and ADEs,particularly for patients with low health literacy, or thoseprescribed high-risk or complex medication regimens.30

Failure to monitor and implement appropriate drugmonitoring was an especially common cause of preventableand ameliorable ADEs.24 A study to identify drug-relatedproblems during and after hospitalization found that pre-ventable ADEs resulted from lack of medication access,nonadherence, and inadequate drug monitoring after dis-charge.31

A study evaluating the economic impact of adverse drugreactions (ADRs) on recurrent hospitalizations in an internalmedicine setting (median patient age of 57 years) found that44.3% of ADRs were preventable.29 When considering ad-missions and readmissions, 11% ( > 973 days) of all treatmentdays were judged to be preventable.29 Additionally, the oc-currence and numbers of ADRs per admission were found toprolong the hospitalization period significantly ( P < 0.001).Twenty percent of 9107 treatment days were caused by in-house (1130 days) and community-acquired ADRs (669days).29

Table 4. Medication Class

SourceSetting/Study

Population Study DesignNumber

of PatientsMedication

ClassAdverse DrugEvent Rates

Gurwitz et al,200312

Multispecialty grouppractice withMedicare enrollees

Prospectivecohort studybetween1999–2000

27,617 Cardiovascularmedications

24.5%

Diuretics 22.15Non-opioid analgesics 15.4%Hypoglycemics 10.95Anticoagulants 10.2%

Bourgeoiset al, 201011

National Center forHealth Statistics Datain the United States;visits between 1995and 2005

Retrospective ADE-relatedvisits were3,544,908

Hospital readmissionCardiotonicglycosides (Digoxin) 12.8%; CI: 8.6–18.6%

Anticoagulants12.8%; CI: 8.6–18.6%Anticonvulsants

6.5%; CI: 3.7–11.2


Urban academic healthsciences center

Secondaryanalysis of aprospectivecohort study

400 Anti-infective 31%Corticosteroids 16%Cardiovascular 16%Analgesic/narcotics 11%Anticoagulants 9%Antiepileptic 4%

Budnitz et al,200524

National ElectronicInjury SurveillanceSystem–All InjuryProgram hospital EDsbetween July toSeptember 2002

Retrospective 598 HospitalizationCardiovascular23.1%Diabetic17.3%Anticoagulants15.4%

Budnitz et al,200726

Nationallyrepresentative,National ElectronicInjury SurveillanceSystem–Cooperative

Retrospective(using Beer’scriteria)

177,504 EDvisits

ED Visit (%)

Adverse Drug EventSurveillance System,2004–2005; National

Warfarin17.3 (12.7–21.9)

Ambulatory MedicalCare Survey, 2004;and NationalHospital Ambulatory

Insulin13.0 (9.4–16.6)

Medical Care Survey,2004.

Aspirin5.7 (3.3–8.2)Clopidogrel4.7 (1.5–7.9)Digoxin3.2 (1.6–4.7)Metformin2.3 (1.4–3.2)

ADE, adverse drug event; CI, confidence interval; ED, emergency department.

344 ROBINSON ET AL.

Table 5. Number of Medications

SourceSetting/Study


of PatientsMedication

Factors

Adverse DrugEvent Related toAdmission Rates

(95% CI)

Bourgeoiset al,201011

National Center forHealth Statistics Datain the United States;visits between 1995and 2005

Retrospective ADE-relatedED visits

were 3,544,908

5 or more drugs

Cardiotonic glycosides(ie, digoxin)

Anticoagulants

Anticonvulsants

Antineoplastics

OR: 1.88(1.56–2.24)

13%(9%–19%)

11%(8%–11%)

7%(4%–11%)

7%(4%–11%)

Hafner et al,20029

University-affiliatedtertiary care

Retrospective: EDcharts: matchedcontrol for: age fordisposition, survival,severity, payer, sex,race, age, number ofdrugs, and total cost

434 Hospitalization:

ED occurring betweenMarch 1 and May 31,1997,

4 or more drugsOR: 2.2(1.7–2.8)

Sarkar et al,201128

National AmbulatoryMedical Care Surveyand the NationalHospital andAmbulatory MedicalCare Survey. From2005 to 2007

Retrospective;secondary dataanalysis

13.5 million ADE-related visits

Ambulatoryvisits

(4.5 million ADEvisits per year)

6-8 meds

OR: 3.83(2.20–6.65)


Urban academic healthsciences center

Secondary analysis of aprospective cohortstudy

400 12 or more medicationsat discharge

Risk of ADE:18%

(11%–27%)

ADE, adverse drug event; CI, confidence interval; ED, emergency department; OR, odds ratio.

Table 6. Utilization

SourceSetting/Study


of PatientsUtilization

Factors

Readmission/*AdverseDrug Event Relatedto Admission Rates

Smithet al,200015

Nine VA medicalcenters- MedicalService

Retrospective: secondaryanalysis from RCT

1378 Last 6 months:ED visits

RR:1.13(1.04–1.24)

Hospitalization RR:1.85(1.43–2.41)

Hafneret al,20029

University-affiliatedtertiary care

ED visits betweenMarch 1 and May 31,1997,

Retrospective: ED charts:matched control for:age for disposition,survival, severity,payer, sex, race, age,number of drugs,and total cost

434 Hospitalization *31%

Zhanet al,20058

Nationallyrepresentativesample of visits

Retrospective: 311,000 to 535,000visits/year

*Per 1,000populationper year

to physician offices,hospital outpatientdepartments, andemergencydepartments

NAMCS and NHAMCSpublic use data from1995 to 2001

Ambulatory care

11.5

Hospitalization

2.8

Sarkaret al,201128

National AmbulatoryMedical Care Surveyand the NationalHospital andAmbulatory MedicalCare Survey. From2005 to 2007

Retrospective;secondarydata analysis

13.5 million ADE-relatedvisits (4.5 millionADE visits per year)

[ ADEs withprimary carevisitscompared tospecialty carevisits

*OR: 2.22(1.70–2.89)

Hospitalization 9%F/u visit for

ADE22%

ADE, adverse drug event; ED, emergency department; F/u, follow-up; NAMCS, National Ambulatory Medical Care Survey; NHAMCS,National Hospital and Ambulatory Medical Care Survey; OR, odds ratio; RCT, randomized controlled trial; RR, risk ratio.

345

Medication discrepancy

Medication discrepancy is defined as a patient-associatedor system-associated discrepancy (Table 7).32 Medicationdiscrepancies between, before, and after discharge often areassociated with ADEs. In a study among community-dwelling adults aged 65 years and older, hospital read-mission rates among patients with identified medicationdiscrepancies was significantly higher (14.3%) than thatamong patients with no identified medication discrepancies(6.1%; P = 0.04).32 Overall, 50.8% of identified contributingfactors for discrepancies were categorized as patient-associ-ated factors, and 49.2% were categorized as system-associ-ated factors. Five medication classes accounted for 50% of allidentified medication discrepancies: anticoagulants (13%),diuretics (10%), angiotensin-converting enzyme inhibitors(10%), lipid-lowering agents (10%), and proton pump in-hibitors (7%).32 The variables significantly associated withpatients who experienced medication discrepancies were thenumber of medications taken (odds ratio [OR], 1.13; 95% CI,1.04–1.23) and the presence of congestive heart failure (OR,2.10; 95% CI, 1.09–4.03). However, the number of medica-tions taken was not associated with readmission rates(P = 0.71).32

Prescriptions

The risk of an ADE increased as the number of medica-tions prescribed increased.24 The top 5 most commonlyprescribed classes of medications at the time of dischargewere cardiovascular agents (1.2 prescriptions per patient),nutrient agents (including electrolyte and vitamin supple-ments [1.1 prescriptions per patient]), gastrointestinal agents(0.9 prescriptions per patient), respiratory agents (0.7 pre-scriptions per patient), and anti-infective agents (0.7 pre-scriptions per patient). ADEs per prescription was highestfor corticosteroids, anticoagulants, antibiotics, analgesics,and cardiovascular medications.24

Outpatient Trends and Environmental Factors

A number of trends place the elderly at high risk forreadmission. With an aging US population, there is an in-creased movement toward outpatient care and medicationusage. Additionally, the numbers of patients with chronicdiseases is increasing, the development and availability ofpotent prescription medications is rising, the transition ofprescription medications to over-the-counter (OTC) avail-ability is growing, discounted generics and mail service are

readily available, and policy changes affecting Medicaredrug coverage benefits have increased uncertainty in theavailability and affordability of medications.26 Subsequently,there is growing concern that these trends will impact safemedication use and put the elderly at risk for hospitaladmission.

Outpatient prescription use

Prescription medicines are the most frequently usedtherapeutic intervention in the outpatient setting. Nearly 2.5billion prescriptions were dispensed by US pharmacies in1998,33 and the percent increase in primary care office visitsthat involved the initiation or continuation of medicationtherapy increased from 61.0% to 72.6% from 1995 to 2005.34

Although the age breakdown is not evident in these reports,in 2011 the Intercontinental Marketing Services (IMS) In-stitute for Healthcare Informatics reported that because ofthe convenience and availability of discounted generics,chain drugstores followed by mail service were increasinglychosen by patients to fill their prescriptions (54% of all pre-scriptions or 2.2 billion) in 2010. Hence, consumption ofmedicines may have led to fewer doctor office visits, whichwere down 4.2% in 2010. The top 5 most expensive drugclasses in 2010 were: oncologics ($22 B), respiratory agents($19.3 B), lipid regulators ($18.7 B), antidiabetic agents ($16.9B), and antipsychotics ($16.1 B). Absolute spending growthgains were highest for antidiabetic agents, antipsychotics,respiratory agents, HIV antivirals, and autoimmune diseaseagents.35

Increase in prescription use

Between the periods 1999–2000 and 2007–2008, the per-centage of Americans using at least 1, 2 or more, and 5 ormore prescription medications in the past month increasedfrom 44% to 48%, from 25% to 31%, and from 6% to 11%,respectively. Prescription drug use increased with age be-tween 1988 and 1994.36 More than 88% of Americans 60years of age and older used at least 1 prescription. Further,more than 76% used at least 2 or more prescription drugs,and 36% consumed 5 or more prescription drugs. Ad-ditionally, women were more likely to use prescription drugsthan men, and the non-Hispanic white population had thehighest prescription drug use in contrast to the MexicanAmerican population, who had the lowest.36 Those whowere without a regular place for health care, without healthinsurance, or without a prescription drug benefit had less

Table 7. Patient and System-Associated Medication Discrepancies

Patient-Associated Discrepancies System-Associated Discrepancies

� Adverse drug effects � Prescribed medication with known allergies/intolerances� Drug intolerance � Conflicting information from different informational sources� Failure to fill prescription � Confusion between brand and generic names� Unnecessary prescription � Incomplete discharge instructions� Money/financial barriers � Inaccurate, duplicate, or illegible transcription� Intentional nonadherence � Incorrect dosage, quantity, or label� Unintentional nonadherence � Unrecognized cognitive impairment� Deficit in managing medications � No caregiver or unrecognized need for assistance

� Unrecognized sight or dexterity limitations

346 ROBINSON ET AL.

prescription drug use compared with those who had thesebenefits. The most commonly used types of prescriptiondrug were cholesterol-lowering drugs, diuretics, and beta-blockers, which usually are used to treat cholesterol, highblood pressure, and heart problems, respectively.36,37

The use of OTC medications has increased because of thetransition of potent prescription medications to OTC statusand the resulting increased availability. Although the overallprevalence of medication use has not changed from 1998,polypharmacy has increased since 2000 from 6.3% to 12% forthe use of at least 5 prescription medications, and from 23%to 29% for the use of 5 or more prescription medications.38

Approximately 82% of US adults take at least 1 medication(ie, prescription or nonprescription drug, vitamin/mineral,herbal/natural supplement) and 29% take 5 or more medi-cations. Americans aged 65 and older are the biggest con-sumers of medications; 17% to 19% of patients in this agegroup take at least 10 or more medications. The most com-monly used drug among prescription and nonprescriptiondrugs is acetaminophen, followed by 2 cholesterol-loweringdrugs (atorvastatin and simvastatin).38

Out of the 41% of US adults who use a vitamin product ina given week, 63% of consumers are older women ( ‡ 65years). Twenty-two percent of US adults use herbals/naturalsupplements, and 32% of prescription drug users also takean herbal/natural supplement.38

In addition to trends such as increased outpatient medi-cation use among the elderly, the elderly are at increasedodds for poor self-management and at risk for hospitalreadmission resulting from age-related physiological chan-ges and co-existing illnesses, a higher prevalence of cognitiveand functional impairment with increasing age, increasingnumbers of chronic diseases, and geographic and functionalisolation (ie, older adults living in the community comparedto nursing home residents).

Other factors that lead to readmissions in the elderlyinclude health care- or patient-related factors. Health care-related factors include: inadequate information and commu-nication by hospital discharge planners to patients, caregivers,and/or post-acute care providers,39,40 inadequate follow-upcare from post-acute and long-term care providers,41 variationin hospital bed supply,47 and medical errors in a hospital thatmay occur during an initial admission and result in illness,injury, or harm to a patient.42 Patient-related factors include:poor patient adherence, insufficient use of the supportive ca-pacity of family caregivers,43,44 and deterioration of a patient’sclinical condition.1

Interventions to Decrease Readmissions

Although there is no consensus on how to decreasereadmissions, there is some evidence that comprehensive,multimodal interventions may be more effective at prevent-ing readmissions than targeting individual components ofthe discharge process. Disease management programs thattarget specific disease conditions have shown potential todecrease morbidity and mortality.45 However, more researchon the utility of these programs is needed to compare theeffect of different aspects of disease management programson different populations. Moreover, disease managementprograms target specific diseases such as diabetes or heartfailure, even though patients face concurrent comorbidities;

this adds to the complexity of achieving success with suchprograms.

Targeted interventions to decrease readmissions haveincluded medication reconciliation,32 pharmacists coun-seling at discharge with a follow-up telephone call,31 anddocumentation of adherence with any or all of the 6 re-quired discharge instructions.46 A meta-analysis reviewed12 randomized controlled intervention studies publishedfrom 1980 through 1990 to determine the efficacy ofplanned interventions to reduce readmissions. These in-terventions included home health teaching, in-hospitalteaching, geriatric consultation, geriatric special care unit,home health visits, pharmacological counseling, struc-tural discharge interview, home visitation, and compre-hensive discharge planning for elderly. In 8 of the 12studies the readmission rates were lower than for thecontrol group.21

Similarly, a review of the literature on interventionalstudies to reduce readmissions also found a 12%–75% re-duction in readmissions in emergency visits. Interventions inthese studies were varied (Table 8).2 Although multimodalinterventions are effective, their utility in terms of cost andresources is unknown. There is a lack of research relatedto identifying and targeting which interventions are mosteffective for those patients at highest risk for readmissions.

Methods and Measurement of Adverse DrugEvent-Related Readmission and Prevention

Although numerous conditions contribute to readmissions,heart failure remains the most common primary dischargediagnosis among Medicare patients.40 However, even withheart failure, readmission rates and associated factors havevaried across institutions because of differences in the spec-trum of patients, disease severity, and comorbid conditions.Additionally, documentation of diagnoses such as a major hipor knee surgery may not take into account patient falls as theunderlying cause of hospitalization. Similarly, the patientsafety literature underestimates ADEs as the cause of read-mission, and differences in institutional reporting make ag-gregation and analyses of disparate data challenging when

Table 8. Interventions to Reduce Readmissions

� Domiciliary aftercare for 2 weeks after discharge� Discharge planning� Home care assistance� Team assessment with recommendations to attending

physicians� Interventions to counteract passivity and enhance active

patient involvement� Case managers� Educational material mailed to discharged patients

followed by telephone call to resolve unmet needs� Review of warning signs and barriers to keeping

appointments� Assessment of the appropriateness of care� Follow-up home visits by a geriatric team (physician,

nurse, physiotherapist)� Postdischarge follow-up by a nurse and a primary care

physician,� Comprehensive geriatric assessment before and after

discharge


estimating the proportion of readmissions resulting frommedication errors. To date, a variety of data sources and studydesigns have been used to examine the incidence, causes, andfactors related to hospital readmissions in both the read-mission and medication safety literature.

Data sources

A majority of researchers have used administrative datafrom large national databases. These data have been ana-lyzed to describe the factors and patterns associated withreadmission, to characterize population estimates on annualreadmission incidence, to identify the risk factors of outpa-tient ADEs, and to examine the factors that underlie betterUS hospital performance on current discharge metrics. Theselarge data sets included claims data,1,22 data from the Na-tional Ambulatory Medical Care Survey, the National Hos-pital and Ambulatory Medical Care Survey,11,28 the HospitalQuality Alliance data set,47 and the National Electronic In-jury Surveillance System–All Injury Program.25

Other studies have used either single or multiple datasources such as administrative databases, electronic medicalrecords, medical charts, patient reports, telephone inter-views, and administrative incident reports from the group’saffiliated pharmacies to examine contributing factors asso-ciated with readmission or ADEs.3,9,18,32,48

In studies that examined home-based interventions, geri-atric care managers gathered data when conducting home-based assessments to determine the prevalence of the use ofOTC drugs, dietary supplements, Part D-excluded medica-tions, and potentially inappropriate medications by home-bound older adults.49 An intervention study also usedpatient self-reports, case summaries, medication lists at ad-mission and discharge, the hospital discharge summary, anyavailable outpatient visit notes, discharge summaries fromED visits or hospital readmissions, and laboratory test resultsto identify drug-related problems during and after hospi-talization.31

Use of a large national survey has the strength to allow forreliable national estimates; however, each visit has limiteddata. For example, a determination of whether the primaryor underlying reason for readmission is symptom manage-ment, progression of disease, inadequate self-management,or attribution of an ADE to a specific medication or treat-ment is not contained in these data sets. Data obtained fromdatabases also rely on documentation and voluntary re-porting of ADEs by the treating physician, which is probablyless sensitive than research studies involving chart review byspecially trained pharmacists or physicians, computer-gen-erated signals, patient interviews, or combination ap-proaches to identify undiagnosed and undocumented ADEs.Moreover, when using estimates to calculate populationrates for ADE visits, multiple ADE visits by the same indi-vidual are not accounted for, and only ADEs that led tohealth care utilization are captured, suggesting that ambu-latory ADEs may be underestimated.

Readmission studies also have relied on medical re-cords and have largely focused on sociodemographic andclinical characteristics. However, contributors to hospitalreadmission that occur in the patient’s environment, such asinadequate monitoring of gradual onset of signs and symp-toms, improper or unsafe medication use that may not lead to

an ADE, asymptomatic errors, or errors with the potential tocause harm, remain undetected or unreported. Consequently,patients face many challenges after discharge (Table 9)50 anddata on such barriers are not easily collected or available.

Understanding the nature and effect of such factors fromthe patient’s perspective would help prioritize interventiontargets for improving outpatient care after discharge to reducereadmissions. Thus, the magnitude of the problem regardingself-management and the severity of the consequences thatlead to readmission in the patient’s environment are un-known. With no structured mechanism to collect and monitoroutpatient characteristics of self-management, it seems logicalthat most errors or problems that can be mitigated go unre-ported unless they are serious enough to bring the patient to aclinical setting.

Study design and methods

With readmission and ADE studies, most approaches in-cluded prospective cohort, retrospective cohort, and second-ary analysis study designs. Few studies had preplannedintervention, or randomized trial study designs. Case-controlstudies, which assess the outcomes of interventions purely interms of reduction in admissions among a cohort of olderpeople without any reference to a control group, often as-sume that patients identified to be at high risk on the basis oftheir previous admissions would continue to be at high riskof admission in the absence of the intervention. An alternativeapproach would be to use 2 separate control groups, one fordirect age comparison and the other for all additional com-parisons. With case summaries, adjudication for the contrib-utors of readmission may rely heavily on medical record or aclinical expert. This may be challenging if adjudicators areaware that the experts had the advantage of follow-up andconsequently place unequal weights on the data source fromthe experts over the medical records. Therefore, improvedmethods of systematic screening for contributors of read-mission should be evaluated and prospective methods forpredictors of readmission should be developed.

Conclusion

Medicare patients have higher readmission rates afterdischarge from the hospital than other age groups. Some ofthe characteristics common among those readmitted are fe-male sex, more comorbidities, chronic conditions, moreADEs, and utilization of ambulatory clinic care and ED ser-vices. Among the elderly, drug-related events were more

Table 9. Patient Challenges After Discharge

� Formidable costs� Lack of insurance coverage affecting medication

procurement and administration� Brief patient visits with inadequate education and

inadequate communication resulting from fragmentationof care across multiple providers, facilities, andpharmacies

� Inadequate patient knowledge� Ineffective health care behaviors� Interaction problems encountered by patients or providers

not readily detected or reported

348 ROBINSON ET AL.

numerous among women and were associated with poly-pharmacy, increased comorbidity, chronic conditions in-volving the circulatory system, and conditions such ascardiac heart failure, diabetes, and atrial fibrillation. ADEsalso were associated with higher numbers of ED and primarycare visits. Admission and readmission rates were at 37%, ofwhich readmission rates were 4.2%. Medication discrepanciesbefore and after discharge were attributed mostly to antico-agulants and diuretics. Similarly, cardiovascular drugs fol-lowed by diuretics and non-opioid analgesics were themedication class of drugs responsible for most ADEs.

Patients with heart failure have the highest readmissionrate. Other conditions such as psychoses, chronic obstructivepulmonary disease, diabetes, and atrial fibrillation also arecommon. Other contributors to readmission and ADEs includepolypharmacy and, in particular, cardiovascular medicationsfollowed by diuretics, non-opioid analgesics, hypoglycemics,and anticoagulants.

With an aging US population, and trends such as in-creasing numbers of patients with chronic diseases, the de-velopment of potent prescription medications, the transitionto and availability of prescription medications as OTC, andchanges to Medicare drug coverage benefits, the rise inreadmission rates is a growing concern.

A majority of factors that contribute to readmissions occurafter discharge and few studies have examined patient-cen-tered factors as patients receive care from multiple providers,decipher complex pharmaceutical names with look-alike andsound-alike medications, manage their medication regimenand dosage changes without assurance of fully understandingthe change, and have intermittent or infrequent communica-tions with their providers about their problems. Additionally,patients value other intangibles (Table 10), which influencetheir motivation to comply with therapeutic medication regi-mens and self-management recommendations.

Strategies to improve monitoring must take into accountthe difficulties the elderly face. Such difficulties include theirsocial setting, frailty and increased comorbidity, risk of de-veloping ADEs from physiological changes affecting thepharmacokinetics and pharmacodynamics of many drugs,requiring assistance with activities of daily living, difficultyattending follow-up clinics that require enhanced commu-nication with community care providers, and poor coordi-nation of home-care services, hospital care, hospital-basedfollow-up clinics, and early telephone contact.

Readmission studies have used predominantly adminis-trative and survey data and medical charts that limit the

predictors of readmission to demographic and clinical vari-ables, ADEs, reported and documented symptoms, andtherapeutic lab values. Factors such as health literacy, de-pression, heart failure knowledge, self-care behaviors, cog-nition, social support, communication between providers,and adequacy of follow-up care have not been exploredsufficiently and may contribute to readmissions.

Structured mechanisms are needed to monitor, collect, andmeasure outpatient characteristics of self-management afterdischarge, as are study designs that consider the etiology ofwhy and how patients respond before, during, and afterreadmission. Similarly, a model that examines the anteced-ents of unintentional or unavoidable contributors to read-mission and the development of strategies to decreasefrequency and severity has the potential to guide the meth-odology. Hence, multiple strategies are required to identifythe predictors of readmission.

Potentially preventable readmissions may require systemchanges that focus on 4 areas: evaluating patients at thetime of discharge; teaching patients about drug therapies,side effects, and what to do if specific problems develop;improving monitoring of therapies; and improving moni-toring of patients’ overall conditions. Similarly, the devel-opment of measures to monitor these interventions also isneeded.

Currently no study has developed models to predict apatient’s risk for readmission or to compare readmission ratesamong different settings. Most studies looking at read-missions have associated patient demographics, clinicalcharacteristics, and healthcare utilization with readmissions.Additionally, studies vary in methods used for case andoutcome identification, use disparate and multiple datasources, and examine readmissions with varying follow-upperiods (ie, 30 days, 60 days, 90 days). Although these char-acteristics may be important predictors of readmission, fewvariables were identified consistently. Examining interveningor mediating contributors to hospital admission from thepatient safety and readmission literature will provide a modelto guide interventions and future research. We have pro-posed a conceptual framework that supports a multivariatemodel to develop a more comprehensive proposal, with theobjective of developing a risk profile or score to enhance theprobability of early identification of those at greatest risk forreadmission and those who might benefit from minimalversus more extensive interventions

Future research that utilizes rigorously designed methodsto identify high-risk patients and targets interventions toreduce the burden of readmissions is likely to achieve thegreatest impact. The costs of potentially preventable hospitaladmissions are considerable. Therefore, patient interventionsto prevent hospital admissions may be cost-effective or evencost saving.

Author Disclosure Statement

Drs. Robinson, Howie-Esquivel, and Vjahov disclosed noconflicts of interest.

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Address correspondence to:Susan Robinson, R.N., Ph.D.

School of NursingUniversity of California, San Francisco

2 Koret Way, Box 0610San Francisco, CA 94143

E-mail: [email protected]


Documents

Readmission Risk Factors after Hospital Discharge Among the Elderly